Underwater leading drone system

ABSTRACT

Systems and methods are provided for least one leading drone configured to move to a leading drone future location based on a future location of a base station. A set of base station future locations may form a base station path for the base station to traverse. Also, a set of leading drone future locations may form a leading drone path for the leading drone to traverse. The base station&#39;s future location may be anticipated from a prediction or a predetermination. The leading drone, navigating along the leading drone path, may collect sensor data and/or perform tasks. The leading drone may interact with sensor drones while traversing the leading drone path. Accordingly, the leading drone may move ahead of the base station in motion, as opposed to following or remaining with the base station.

FIELD

The present application relates generally to unpiloted devices such asdrones, and more specifically to a system of a leading drone thatnavigates based on base station movement.

BACKGROUND

Drones are unpiloted devices and may be used by the military, police,rescue, scientific, and commercial communities. One example of a droneis an unmanned device capable of controlled, sustained, and poweredmovement. As such, the designs of drones may consist of vehicles,aircraft, boats, submarines or spacecraft of various sizes,capabilities, and weights. A typical drone consists of a propulsiondevice, such as an engine, a navigation system, one or more sensors, andpossibly cargo. For an aircraft or aerial drone, the sensors may provideinformation to a ground observer about the terrain the drone overflies,such as video information about a lost hiker in a rescue application,information from laser and/or biological sensors about environmentalconditions in a scientific or security application, or a combination ofvideo, laser, biological and other sensors concerning battlefieldconditions in a military application. The cargo may be munitions, food,medicine, and/or other goods depending on the mission of the drone.

As the drone is unmanned, computer software executing on one or moreprocessors aboard the drone partially or completely controls the drone.The computer software may control the various functions performed by thedrone, perhaps with the aid of an observer.

There continues to be a need for expanded capabilities of unmannedaerial drones.

SUMMARY

Various implementations of systems, methods and devices within the scopeof the appended claims each have several aspects, no single one of whichis solely responsible for the desirable attributes described herein.Without limiting the scope of the appended claims, some prominentfeatures are described herein.

Details of one or more implementations of the subject matter in thisspecification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages will becomeapparent from the description, the drawings, and the claims. Note thatthe relative dimensions of the following figures may not be drawn toscale.

In a particular embodiment, a system including a leading drone isdisclosed. The leading drone is configured to identify a base stationconfigured to move from a current location, determine a future locationof the base station, and move to a drone location relative to the futurelocation.

In another particular embodiment, the drone location is at the futurelocation.

In another particular embodiment, the leading drone is configured tomove to a location where the base station has traveled on, such that theleading drone travels on the same traveling path as the base station,only lagging behind in either distance or time.

In another particular embodiment, the leading drone is configured toreceive a control signal from the base station including the futurelocation.

In another particular embodiment, the leading drone is configured todetermine the future location based on the current location.

In another particular embodiment, the leading drone is configured todetermine a base station path between the current location and thefuture location, and move along a drone path relative to the basestation path.

In another particular embodiment, the leading drone is configured todetermine the future location along a base station path that includesthe current location.

In another particular embodiment, the leading drone is configured todetermine a drone path relative to the base station path.

In another particular embodiment, the drone path is parallel to the basestation path.

In another particular embodiment, the drone path crisscrosses the basestation path.

In another particular embodiment, the drone path circles the basestation as the base station traverses the base station path.

In another particular embodiment, the leading drone is configured toreceive a control signal from the base station that includes the basestation path.

In another particular embodiment, the leading drone includes a sensor.The leading drone is configured to: collect sensor data along the basestation path using the sensor; identify a trigger based on the sensordata; and move to a trigger location based on the trigger.

In another particular embodiment, the leading drone is configured toreturn to the drone path.

In another particular embodiment, the sensor is a directional radar.

In another particular embodiment, the leading drone is configured toscan for sensory data across the base station path.

In another particular embodiment, the leading drone is configured totravel along the drone path ahead of the base station.

In another particular embodiment, the leading drone is configured totravel along the drone path alongside the base station.

In another particular embodiment, the leading drone is configured totravel along the drone path behind the base station.

In another particular embodiment, the leading drone comprises a sensor.The leading drone is configured to: collect sensor data along the dronepath using the sensor; retrieve geographical data from a data store; andcross reference the sensor data with the geographical data to produceupdated geographical data.

In another particular embodiment, the leading drone is configured tosend the updated geographical data to the base station.

In another particular embodiment, base station is a land vehicle and theleading drone is an unmanned aerial vehicle.

In another particular embodiment, the leading drone is configured todetermine the future location relative to received geographical data.

In another particular embodiment, the leading drone is configured toreceive a control signal from the base station for control of theleading drone.

In another particular embodiment, the leading drone is configured toreceive an override signal that overrides the control signal andcontrols the leading drone.

In another particular embodiment, the system includes a second leadingdrone, the second leading drone configured to receive the overridecommand that controls the second leading drone.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing aspects and many of the attendant advantages will becomemore readily appreciated as the same become better understood byreference to the following detailed description, when taken inconjunction with the accompanying drawings, wherein:

FIG. 1 illustrates an example of a leading drone interacting with a basestation as part of a convoy of vehicles.

FIG. 2 illustrates an example of a leading drone oriented relative to abase station.

FIG. 3A illustrates an example of a leading drone oriented to a side ofa base station.

FIG. 3B illustrates an example of multiple leading drones on differentsides of a base station.

FIG. 3C illustrates an example of multiple base stations interactingwith a single leading drone.

FIG. 4 illustrates an example of a leading drone executing a zig zagleading drone path relative to a base station path.

FIG. 5 illustrates an example of a leading drone executing a circlingleading drone path.

FIG. 6 illustrates an example of a leading drone traversing a basestation path ahead of the base station.

FIG. 7 illustrates an example of a trigger event along a leading dronepath.

FIG. 8 illustrates features of base station future location prediction.

FIG. 9 illustrates an example of a leading drone interacting with asensor drone.

FIG. 10 illustrates an example of a leading drone communicating withmultiple sensor drones.

FIG. 11 illustrates an example of a leading drone communicating withmultiple sensor drones tethered to communication relays.

FIG. 12 illustrates an example of a leading drone communicating with acommunication relay servicing multiple sensor drones.

FIG. 13 illustrates an example of a leading drone communicating withstationary sensor drones.

FIG. 14 is a block diagram of example systems utilized in a leadingdrone system.

FIG. 15 is a flowchart of an example process for determining a leadingdrone path.

FIG. 16 is a flowchart of an example process for determining basestation future locations on the fly.

FIG. 17 is a flowchart of an example process for a triggered task.

FIG. 18 is a flowchart of an example process for combining leading dronesensor data and sensor drone sensor data.

FIG. 19 illustrates a block diagram of an example system architecturefor a drone.

DETAILED DESCRIPTION

Generally described, aspects of the present disclosure relate to systemsand methods for at least one leading drone configured to move to aleading drone future location based on a future location of a basestation. A set of base station future locations may form a base stationpath for the base station to traverse. Also, a set of leading dronefuture locations may form a leading drone path for the leading drone totraverse. The paths may be in a substantially two-dimensional space(such as over land) or in three-dimensional space (such as in the air orunder water). The base station's future location may be anticipated froma prediction or a predetermination. For example, the base station'santicipated traversal along a base station path may encompass predictedfuture traversals (such as a prediction based upon current and/or pasttraversals) and/or predetermined future traversals (such asconfiguration for performance of a traversal at a future time that arestored in, and retrieved from, a data store). Accordingly, the leadingdrone may move ahead of the base station in motion, as opposed tofollowing or remaining with the base station.

In this specification, drones include any unmanned vehicle, such as anunmanned aerial vehicles (UAV), unpiloted aerial vehicle, remotelypiloted aircraft, unmanned aircraft systems, any aircraft covered underCircular 328 AN/190 classified by the International Civil AviationOrganization, and so on. As an example, the drone may be in the form ofa single or multi-rotor copter (e.g., a quad-copter) or a fixed wingaircraft. In addition, certain aspects of the disclosure can be utilizedwith drones in the form of other types of unmanned vehicles (e.g.,wheeled, tracked, and/or water vehicles).

The leading drone, navigating along the leading drone path, may collectsensor data and/or perform tasks. Examples of tasks include providing abase station with information concerning a base station path fortraversal or to execute a navigational pattern traversing a leadingdrone path. The sensor data may be collected from sensors accessible to(e.g., mounted on or in) the leading drone. The sensors may bedirectional sensors that may sense in a particular direction (such as acamera configured to capture a field of view) or omnidirectional sensorsthat do not sense in a particular direction. Directional sensors may beconfigured to move and scan an area over time, such as by rotating 360degrees along one or two axes. The sensor data may be cross referencedwith stored or known sensor data, such as known geographical data orlandmarks that the leading drone's sensors would be expected toidentify. As the leading drone navigates along the leading drone path,the sensor data may be captured from various perspectives relative tothe base station, such as in front of, behind, above, or alongside thebase station. For example, the leading drone may collect sensor datafrom behind the base station to ensure that there is no vehiclefollowing the base station, or may collect sensor data ahead of the basestation to make sure there are no obstacles that would affect the basestation's traversal of the base station path. This combination mayproduce more robust sensor data that combines both the known or storedsensor data with the current or new sensor data collected by the leadingdrone traversing the leading drone path. Accordingly, a leading dronemay send this combined sensor data to a base station and/or autonomouslyprovide the base station with advantageous sensor data not availablefrom the vantage point of the base station or perform tasks that thebase station would not be able to perform.

In certain embodiments, the leading drone may perform a task, such aschanging its leading drone path, when autonomously triggered based oncollected sensor data or when commanded by a control signal receivedfrom a base station. After performance of the triggered task, theleading drone may return to the leading drone path and begin from wherethe leading drone path was interrupted due to the triggered task.Alternatively, after performance of the triggered task, the leadingdrone may continue along the leading drone path starting from a leadingdrone future location that the leading drone had planned on traversingat the time of triggered task completion. In certain embodiments,multiple leading drones may be utilized to identify and respond tomultiple triggers.

In certain embodiments, a base station may be configured for autonomousnavigation based on the leading drone sensor data. For example, the basestation may be an autonomous driving vehicle that utilizes the leadingdrone's sensor to navigate along the base station path. Utilizing sensordata from the leading drone may be advantageous in situations whereleading drone sensors are able to collect sensor data from areas thatare not accessible to sensors onboard the base station. For example, asensor such as a video camera on a base station may be limited to senseareas around the base station within a line of sight of the videocamera, while a video camera sensor mounted on a leading drone may beable to sense areas beyond the base station video camera sensor's lineof sight.

In certain embodiments, processors onboard the base station may offloadprocessing tasks to the leading drone for processing by leading droneprocessors. For example, sensor data captured by the leading drone mayfirst be processed at the leading drone and the analysis from the sensordata sent to the base station rather than sending the raw sensor data tothe base station.

The leading drones may be part of a leading drone network that includesleading drones, base stations, and/or sensor drones. For example, asingle base station may interact with multiple leading drones. Each ofthe multiple leading drones may interact with multiple sensor drones.Accordingly, the base station may benefit from sensor data collectedfrom multiple leading drones and multiple sensor drones. Also, a leadingdrone may interact with multiple base stations, such as where thenavigational activity of multiple base stations may configure theleading drone to undertake specific a leading drone path.

As described, the leading drone may interact with sensor drones whiletraversing the leading drone path. The sensor drones may be stationaryor configured for motion. The sensor drones may transfer sensor dronesensor data to the leading drone to further augment the leading drone'ssensory capabilities. For example, a sensor drone may traverse an areaand deploy sensors to characterize the vicinity of the traversed area togenerate sensor drone sensor data. The generated sensor drone sensordata may be stored by the sensor drone. The sensor drone may transferstored sensor drone sensor data during the traversal, such as historicalenvironmental data collected by the sensor drone's sensors, to theleading drone when the leading is within a distance at which the sensordrone's communication systems operate. Accordingly, the leading dronemay advantageously augment its collection of sensory data whiletraversing the leading drone path.

In certain embodiments, the leading drone may control a sensor drone.This may be active control of the sensor drone by the leading drone. Forexample, an underwater sensor drone may be physically tethered to anaerial leading drone so that the leading drone can propel, or drag, theunderwater drone across an area underwater to collect underwater sensordrone sensor data in that area.

FIG. 1 illustrates an example of a leading drone 102 interacting with abase station 104. The base station 104 may be part of a convoy ofvehicles 104, 106. The leading drone 102 may communicate with the basestation via a leading drone communication link 110. Although the basestation is illustrated as a vehicle in FIG. 1, the base station can bein any form factor that can establish a communication link 110 with theleading drone, such as a handheld device, personal computer, watercraft,or airplane.

The leading drone communication link 110 may include any type ofcommunication protocol from which devices can communicate with eachother, such as one or combinations of infrared (IR) wirelesscommunication, broadcast radio, satellite communication, microwavewireless communication, microwave radio, radio frequency, wi-fi,Bluetooth, Zigbee, GPC, GSM, RFID, OFDM or the like. In certainembodiments, the leading drone communication link 110 may include one ormore links of narrow band, wide band, or a combination of narrow or wideband communications. Also, the leading drone communication link 110 mayinclude antennas of different types, such as directional and/oromnidirectional antennas.

The leading drone may have various sensors connected to it for datacollection. For example, photographic cameras, video cameras, infra-redcameras, multispectral cameras, lidar, radio transceiver, sonar, andTCAS (traffic collision avoidance system). In the illustratedembodiment, the leading drone 102 includes a video camera 112 configuredto survey an area 114 underneath the base station 102 within a field ofview of the camera 112.

As will be explained in more details later, the leading drone 102 may beconfigured to move to leading drone future locations along a leadingdrone path based on a future location of the base station (which may bealong a base station path). Accordingly, the leading drone may remainahead of a base station while the base station is moving, rather thanbehind or alongside a moving base station.

In certain embodiments, multiple base stations 104, 106 may interactwith the leading drone 102. For example, the leading drone 102 may beconfigured to navigate based on a future location of the first basestation 104 during one time interval but then be configured to navigatebased on a future location of the second base station 106 at a secondtime interval. This example may occur after the first leading drone 104stops moving or is out of commission due to a car crash.

The leading drone 102 may autonomously remain in a position at a setdistance ahead of the base station 104 based on where the base station104 will be, rather than where the base station 104 is or has been. Thebase station may remain in communication with the leading drone,allowing the base station to send commands to the leading drone. Forexample, the commands may include modifications to the leading dronepath or to perform specific tasks. These tasks may include surveyinglandscapes, waterways, or airspaces ahead of the base station for dangersuch as rocks in the water, floating objects in the water, icebergs inwater, wash-out roads, downed powerlines, downed trees, refugees inwater, extreme weather conditions; search and rescue operations;dropping medical supplies, food supplies, life jackets, and life saversto people in water; taking and transmitting aerial photos and videos;searching for schools of fish or game; or searching for oil spills. Incertain embodiments, the leading drone 102 may be equipped with sensorsto search, locate and identify people or animals on the ground that mayneed assistance, or that may be hostile to the base station 104 or theconvoy of vehicles 104, 106.

The leading drone 102 may have access to an obstacle avoidance system sothe leading drone 102 can avoid crashing into obstacles such asbuildings, trees, utility poles, and power lines. The obstacle avoidancesystem can compare readily available data (e.g., 3-D maps, Google® Mapsdata produced by Google Inc. headquartered in Mountain View, Calif., orsatellite images) with data the leading drone has collected from thesensors (e.g., via visual image/video detection, visual sensors andcomputation/processing, lidar, radar, sonar, infrared sensor) to map outpotential obstacles to avoid.

In certain embodiments, the leading drone 102 may include tools toperform a task. The tools may include passive devices that do notmanipulate objects around the leading drone, such as a sensor, or activedevices that can manipulate an area around a leading drone, such as alaser or spot light to identify objects for ground support personnel ora loud speaker to transmit sounds generated at the base station throughthe loud speakers to targets in an areas being surveyed.

In certain embodiments, the leading drone 102 may land on the basestation 104 on demand or may land on a moving vehicle for storage,recharging or maintenance.

In certain embodiments, other vehicles in the convoy other than the basestation may be an alternate base station. For example, if the basestation 104 is out of commission (for example, due to a car crash) theleading drone may interact (e.g., determine the leading drone path basedon an anticipated base station path and/or send leading drone sensordata to the base station) with the other vehicle in the convoy as analternate base station 106. These alternate base stations may have anorder of priority such that the leading drone communicates with thehighest priority alternate base station among available alternate basestations within range of the leading drone's communication systems.These priorities may be based upon various criteria (e.g., time of day,alternate base station paths, current payload of the leading drone) andmay be autonomously determined by the leading drone or received by theleading drone via a control signal from a base station.

In certain embodiments, the nodes or communication points (e.g., basestation, leading drone, sensor drone) can optionally have acommunication module using LTE, satellite, or any wireless communicationcapability (hardware and/or software) currently known or to be developedin the future. Having this optional connectivity can further ensureoptimal, reliable, and timely real-time connectivity of any of thesenodes of the leading drone network to each other within the leadingdrone network, or to ensure optimal, reliable, and timely real-timeconnectivity to others (e.g., a command center such as a police stationlocated remotely and communicable with the nodes over a network such asthe Internet).

In certain embodiments, the nodes of the leading drone network canselect (either autonomously or non-autonomously), in real time,different communication types. This selection can be based on criteriasuch as cost of transmission, reliability of transmission, speed oftransmission, reception of transmission, or security of thetransmission. Also, the nodes of the leading drone network may also havecommunication modules that support LTE and satellite communicationeither as a primary or a supplementary mode of communication. Forexample, as the base station, leading drone, and/or sensor drone travelsthrough regions amenable to certain types of communication protocols(such as LTE), the base stations, leading drones, and/or sensor droneswould operate with different communication protocols (such as LTE), forreasons such as lower cost of communication and/or higher reliability ina low-altitude airspace. In certain embodiments, a communication typecan be selected that enables an external actor, such as a command postor headquarters located remotely in a different city, to communicate inreal time with the nodes of the leading drone network. Suchcommunication may allow the external actor to receive, in real time,audio/video data captured by the leading drone or to send commands forthe leading drone to perform a task.

FIG. 2 illustrates an example of a leading drone 202 oriented relativeto a base station 204. The base station 204 may be traveling along abase station path 208 that is parallel to and bound within a landmarksuch as a road 210. The base station path 208 may include multiple basestation future locations 214A-E to be traversed over a time period. Theleading drone may be travelling along a leading drone path 212 thatincludes leading drone future locations 222A-E. These leading dronefuture locations may be based upon the base station future locations214A-E and traversed over the same time period that the base stationfuture locations 214A-E are to be traversed.

For example, as the base station 204 is anticipated to traverse the basestation path 208, the base station 204 may move from base station futurelocation 214A to base station future location 214B to base stationfuture location 214C to base station future location 214D and to basestation future location 214E. Accordingly, the leading drone 202 may beconfigured to traverse the leading drone path 212 by moving from leadingdrone future location 222A to leading drone future location 222B toleading drone future location 222C to leading drone future location 222Dand to leading drone future location 222E. Timing at which the leadingdrone 202 traverses the leading drone path 212 may include being atleading drone future location 222A when the base station is anticipatedto be at base station future location 214A, being at leading dronefuture location 222B when the base station is anticipated to be at basestation future location 214B, being at leading drone future location222C when the base station is anticipated to be at base station futurelocation 214C, being at leading drone future location 222D when the basestation is anticipated to be at base station future location 214D, andbeing at leading drone future location 222E when the base station isanticipated to be at base station future location 214E.

Each of the leading drone future locations may be a set distance or timeahead of the base station future locations. By being a set distanceahead, a leading drone future location may be a set distance separatedfrom a base station future location along a direction that the basestation is anticipated to travel. For example, leading drone futurelocation 222A may be a set distance (such as 50 meters) ahead of basestation future location 214A as determined by the direction at which thebase station path 208 is traveling (indicated by the arrow at the end ofthe base station path 208). By being an amount of (or set) time ahead, aleading drone may be at a leading drone future location which is locatedwhere a base station future location is anticipated to be located at afuture time. For example, leading drone future location 214A may be anamount of time ahead (such as 10 seconds) by being located at where thebase station 204 is anticipated to be 10 seconds after traversing basestation future location 214A.

The base station's 204 anticipated traversal along a base station pathmay encompass predicted future traversals (such as a prediction basedupon current and/or past traversals) and/or predetermined futuretraversals (such as configuration for performance of a traversal at afuture time). For example, the base station's future traversals may bepredetermined, such as predetermined via a navigation module thatconfigures the base station to traverse the base station futurelocations at future times. For example, the base station may have ageospatial sensor (e.g., GPS) that senses where the base station is.Then, based also on where its intended destination is relative to othergeospatial information such as a map, a navigational module may plot anavigational path for the base station to traverse over time to arriveat the intended destination. Example navigational modules may includethe Garmin® Navigator application produced by Garmin Ltd. headquarteredin Olathe, Kans. or the Google® Maps Navigation application developed byGoogle Inc. headquartered in Mountain View, Calif.

Also, for example and as will be discussed further below in connectionwith FIG. 8, the base station's 204 anticipated base station path may bepredicted from determining a difference between a base station pastlocation and a base station current location during a past interval oftime (such as over the last minute). The difference may be plotted as abase station path for traversal over a future interval of time (of asame duration as the past interval of time), ending at ananticipated/predicted base station future position and starting from thebase station current location.

Accordingly, in the illustrated embodiment of FIG. 2, the leading drone202 is configured to move (e.g., traverse) along a leading drone path212. The leading drone path 212 may be along leading drone futurelocations 222A-E that are a set distance and time ahead of base stationfuture locations 214A-E. The base station future locations 214A-E may bealong a base station path 208 that the base station 204 is anticipatedto traverse.

In certain embodiments, directional sensors onboard the leading drone202 may be configured to perform a sweep of an area ahead of the leadingdrone or around the leading drone as the leading drone traverses aleading drone path, such as by rotating across 360 degrees of freedomacross one or two axis or by sweeping side to side.

FIG. 3A illustrates an example of a leading drone 302 oriented to a sideof a base station 304. The base station 304 may be anticipated totraverse a base station path 306 with at least one base station futurelocation 308 along the base station path. The base station path may bealong a road 310 or other geographic landmark. The leading drone 312 maybe configured to traverse a leading drone path 314 with at least oneleading drone future location 316. The leading drone 312 traversing theleading drone path 314 may be ahead of the base station 304 in thedirection of the base station path 306 (as indicated with the arrow ofthe base station path 306) but offset to a (right) side of the basestation 304. The leading drone future location(s) 316 which outline theleading drone path may be based on the anticipated base station futurelocations 308, which outline the base station path 306.

In contrast to the embodiment illustrated in FIG. 2 where the leadingdrone 202 traverses a leading drone path 212 that is both a set distanceand time ahead of the base station 204 (traversing the base station path208) the embodiment illustrated in FIG. 3A shows how the leading drone312 may be ahead of the base station 204 at a set distance but not a settime, or otherwise be offset to a side of the base station 304traversing the base station path 306. The leading drone 312 may beconfigured to be at the leading drone future location 316 when the basestation 304 is anticipated to be at the base station future location308.

FIG. 3B illustrates an example of multiple leading drones on differentsides of the base station. FIG. 3B is similar to FIG. 3A except thatanother leading drone 332 may be configured to traverse a leading dronepath 334 with at least one leading drone future location 336. Theleading drone 332 traversing the leading drone path 334 may be ahead ofthe base station 304 in the direction of the base station path 306 (asindicated with the arrow of the base station path 306) but offset to a(left) side of the base station 304. Accordingly, the leading dronefuture location(s) 316 which define the leading drone path 314 and theleading drone future locations 336 which define the leading drone path334 both may be based on the anticipated base station future locations308 which define the base station path 306. The leading drones 312, 332may be configured to be at the leading drone future locations 316, 336when the base station 304 is anticipated to be at the base stationfuture location 308.

FIG. 3C illustrates an example of multiple base stations interactingwith a single leading drone. The base stations 354, 360 may beanticipated to travel along base station paths 356, 362 with at leastone base station future location 358, 364 respectively. The base stationpaths 356, 362 may be along a geographic landmark such as along prongsleading to a fork in a road 352. One leading drone 372 may be configuredto travel along a leading drone path 374 initially ahead of one basestation 354. However, the leading drone path 374 may be determined basedon both base station paths 356, 362 (rather than a single base stationpath 356) such that leading drone future location 376 is based on bothbase station future locations 358, 364 (rather than a single basestation future location 358). For example, the leading drone 372 mayinitially be configured to be ahead of the first base station 354 but,as the base station paths 356, 362 converge, the leading drone 372 mayswitch to be ahead of the second base station 360.

FIG. 4 illustrates an example of a leading drone 402 executing a zig zagleading drone path 410 relative to a straight base station path. Thebase station 404 may be anticipated to traverse a base station path 418with at least two base station future locations 408, 412. The basestation path may be bound by a geographic landmark, such as a road 406.The leading drone 402 may be configured to traverse a leading drone path410 with at least two leading drone future locations 414, 416.

The leading drone path 410 may be along a zig zag pattern relative tothe base station path 418 and not be parallel to the base station path418. The leading drone future location 414 may be to one side of thebase station 404 when anticipated to be at a base station futurelocation 414 and then, later along the leading drone path 410, theleading drone future location 416 may be to another side of the basestation 404.

FIG. 5 illustrates an example of a leading drone 502 executing acircling leading drone path 510. The circling leading drone path 510 mayinclude a circular pattern that maintains a circular relativeorientation over time from anticipated base station future locations 510as the base station 504 traverses the base station path 506.Advantageously, the circling leading drone path 512 may focus a sensorto collect sensor data of the center region of the circle formed by thecircling drone path for various perspective sensor sweeps of an areaahead of the base station 504 as the base station traverses the basestation path 506.

FIG. 6 illustrates an example of a leading drone 602 traversing a basestation path ahead of the base station 604. The base station 604 maytraverse a base station path that includes base station future locationsfrom the start position 606 to the end position 620 along the road 622.The leading drone 602 may traverse a leading drone path from the startposition 606 to the end position 620 along a leading drone path withleading drone future locations 614, 620, 612 that do not all maintain aset distance from the base station future locations 608, 624, 610, whilethe base station 604 traverses its base station path. Although a set endposition is illustrated, end positions may be modified or setdynamically as the base station operates, such as being set by the basestation navigational module or as anticipated by a leading drone.

The leading drone 602 may traverse a leading drone path that firstentirely traverses the road 622 from the start position 606 to the endposition 620 and then returns to maintain a set distance ahead of thebase station 604 as the base station 604 completes its traversal fromthe start position 606 to the end position 620. For example, at a firsttime after the base station moves from the start position 606, theleading drone 602 may be configured to be at a first leading dronefuture location 614 while the base station may be anticipated to be at afirst base station future location 608. At a second time later than thefirst time, the leading drone 602 may be configured to have traversed toa second leading drone future location 618 that is over the end position620 while the base station is at a second base station future location610. At a third time later than the second time, the leading drone 612may be at a third leading drone future location 612 ahead of the basestation 604 when the base station is anticipated to be at a third basestation future location 624. The leading drone 602 may then beconfigured to traverse a portion of the leading drone path thatmaintains a set distance ahead of the base station 604 until the basestation 604 reaches the end position 620.

FIG. 7 illustrates an example of a leading drone 702 performing atriggered task. The trigger may be any event whose occurrence promptsthe leading drone 702 to perform a task that the leading drone wouldotherwise not perform without trigger occurrence. The task mayreconfigure the leading drone to adopt a new leading drone path, performa new task or to modify the previous leading drone path or task prior todetection of the trigger.

Similar to FIG. 6, in FIG. 7 the base station 604 may traverse a basestation path that includes base station future locations from the startposition 606 to the end position 620 along the road 622. The leadingdrone 702 may traverse a leading drone path from the start position 606to the end position 620 along a leading drone path initially asdescribed in connection with FIG. 6.

However, as illustrated in FIG. 7 referencing the discussion of FIG. 6,at the first time, the leading drone 702 may be configured to be at afirst leading drone future location 714 and the base station may beanticipated to be at a first base station future location 608. When atthe first leading drone future location 714, the leading drone 702 maydetect an unidentified vehicle 724 using sensors onboard the leadingdrone. The detection of the unidentified vehicle may be a trigger eventwhich reconfigures the leading drone to perform a task to investigatethe unidentified vehicle rather than to move to the end position 620directly. As part of performance of the triggered task, the leadingdrone 602 may be configured to notify the base station of the triggerevent and to move to a second leading drone future location 618 toinvestigate the unidentified vehicle 724 from a different perspectivethan the perspective afforded at the first leading drone future location714. The performance of the triggered task may be in progress at thesecond time. After the triggered task is complete, at the third time,the leading drone 702 may be at a third leading drone future location712, which is ahead of the base station 604 when the base station 604 isanticipated to be at a third base station future location 624. Theleading drone 702 may then be configured to maintain a set distanceahead of the base station 604 until the base station 604 reaches the endposition 620.

FIG. 8 illustrates features of base station future location prediction.As discussed above, anticipation by base station future locationprediction may be contrasted with anticipation by predetermined basestation future locations for traversal at future times. The basestation's anticipated base station path may be predicted fromdetermining a difference between base station current location and basestation past location(s) during an interval of time (such as over thelast minute) and extending that difference from the current location fora traversal across the interval of time in the future.

As illustrated in FIG. 8, the base station 806 may be at a base stationcurrent location relative to a base station past location 802 and ananticipated base station future location 810. The difference between thebase station past location 802 and the base station current location 806may be represented by a past vector 804 of a distance (illustrated asthe length of the past vector 804) and a direction (illustrated as thearrow at the end of the past vector 804) over a past period of time(e.g., 10 seconds past). The parameters of the past vector 804 (e.g.,distance and direction) may be applied to the current location of thebase station 806 as a future vector 808 that includes a distance(illustrated with the length of the future vector 808) and a direction(illustrated with an arrow at the end of the future vector 808) over afuture period of time of the same duration as the past period of time(e.g., 10 seconds in the future). Accordingly, a predicted (e.g.,anticipated) base station future location 810 may be determined as theend point of the future vector 808.

FIG. 9 illustrates an example of a leading drone 902 with a sensor drone906. The leading drone 902 may communicate with a base station 904 (inthe form of a watercraft on a water surface 914) via a leading dronecommunication link 908. Although the base station is illustrated as awatercraft in FIG. 9, the base station can be in any form factor thatcan establish a communication link 110 with the leading drone, such as ahand/mobile device, personal computer, vehicle, or airplane.

The leading drone communication link 908 may include any type ofcommunication protocol from which devices can communicate with eachother, such as one or combinations of infrared (IR) wirelesscommunication, broadcast radio, satellite communication, microwavewireless communication, microwave radio, radio frequency, wi-fi,Bluetooth, Zigbee, GPC, GSM, RFID, OFDM or the like.

The leading drone 902 may have various sensors connected to it for datacollection. For example, photographic cameras, video cameras, infra-redcameras, multispectral cameras, lidar, radio transceivers, and sonar.The leading drone 902 may also be equipped with a TCAS (trafficcollision avoidance system). In the illustrated embodiment, the leadingdrone 902 includes a video camera 912 configured to survey an area 910underneath the leading drone 902 within a field of view of the camera912.

The leading drone 902 may be configured to move to leading drone futurelocations along a leading drone path based on base station futurelocations, which may be along a base station path. Accordingly, theleading drone may remain ahead of a base station while the base stationis moving, rather than behind or alongside a moving base station. Also,the leading drone 102 may autonomously remain in a position at a setdistance ahead of the base station 904 based on where the base station104 will (or is anticipated to) be, rather than where the base station904 is or has been.

The leading drone 902 may communicate with a sensor drone 906 via asensor drone communication link 920 that may be in the form of a cablewire 920. The sensor drone 906 may be underwater while the leading drone902 is aerial. The sensor drone 906 may include any form of sensorexternal to the leading drone 902 from where the leading drone 902 cancollect sensor data that the leading drone 902 would otherwise not havecollected from sensors on the leading drone 902.

The sensor drone communication link 920 may additionally or optionallyinclude any type of wireless communication protocol from which devicescan communicate with each other, such as one or combinations of infrared(IR) wireless communication, broadcast radio, satellite communication,microwave wireless communication, microwave radio, radio frequency,wi-fi, Bluetooth, Zigbee, GPC, GSM, RFID, OFDM or the like. In theillustrated embodiment of FIG. 9, the sensor drone is physicallyconnected with the leading drone via a cable wire 920 and the sensordrone communication link includes communication protocols from whichdevices can communicate over the cable wire 920. In certain embodiments,the wired sensor drone communication link 920 may also supply power tothe sensor drone 906.

The sensor drone 906 may be propelled through the water by beingpassively dragged by a moving leading drone 902 via the cable wire 920.Optionally, the sensor drone 906 may also be able to actively move viaself propulsion, such as via propellers on the sensor drone 906 that canpropel the sensor drone 906 through the water. The self propulsion maybe automated without input external to the sensor drone 906 or may beactively controlled by input external to the sensor drone 906 such asfrom the leading drone 902 (via the wired sensor drone communicationlink 920 or a wireless sensor drone communication link) and/or from thebase station (via the leading drone communication link and the wiredsensor drone communication link 920 or wireless sensor dronecommunication link).

The sensor drone 906 may have various sensors connected to it for datacollection. For example, photographic cameras, video cameras, infra-redcameras, multispectral cameras, lidar, radio transceivers, or sonar. Inthe illustrated embodiment, the leading drone 902 includes a sonarconfigured to survey an area around the leading drone 902 using activesonar pulses 912.

Accordingly, the aerial leading drone 902 may be configured to collectaerial sensor data from a target location 910 (whether above orunderwater, e.g., aerial view of a school of fish), while the submersedsensor drone 906 is configured to collected underwater sensor data fromthe target location 910. The submersed sensor drone 906 may beconfigured to send the underwater sensor data to the aerial leadingdrone 902 (e.g., via the sensor drone communication link 920). Thisunderwater sensor data may be sensor data that the aerial drone may nototherwise have access to, due to reasons such as being underwater or useof sensors specific for underwater sensing. The aerial leading drone 902may be configured to produce target location data from the aerial sensordata and the underwater sensor data.

In certain embodiments, the submersed sensor drone 906 may be configuredto selectively travel closer to the surface of the water or further fromthe surface of the water to reduce friction during underwater travel,depending on the condition of the water.

FIG. 10 illustrates an example of the leading drone 902 communicatingwith multiple sensor drones 1002A, 1002B. FIG. 10 is similar to FIG. 9except that in FIG. 10 the leading drone 902 communicates wirelesslywith two sensor drones 1002A, 1002B, over wireless sensor dronecommunication links 1004A, 1004B.

Each of the sensor drones 1002A, 1004B may be self propelled andconfigured to collect underwater sensor data from the vicinity of thetarget area 910. Each of the sensor drones 1002A, 1004B may communicateover wireless sensor drone communication links 1004A, 1004B with thesensor drone 902. In certain embodiments, the wireless sensor dronecommunication links 1004A, 1004B may have a limited range from thesensor drone 1002A, 1002B from which they are centered on. The wirelesssensor drone communication link 1004A may be established when theleading drone moves within range of the wireless sensor dronecommunication link 1004A centered on the sensor drone 1002A. Also, thewireless sensor drone communication link 1004B may be established whenthe leading drone moves within range of the wireless sensor dronecommunication link 1004B centered on the sensor drone 1002B.

Accordingly, the single aerial leading drone 902 may interact withmultiple sensor drones 1002A, 1002B when in range of both sensor dronecommunication links 1004A, 1004B. The submersed sensor drones 1002A,1002B may be configured to send underwater sensor data to the aerialleading drone 902. The aerial leading drone 902 may be configured toproduce target location data from the aerial sensor data (collected fromthe aerial leading drone) and the underwater sensor data.

FIG. 11 illustrates an example of the leading drone 902 communicatingwith the multiple sensor drones 1002A, 1002B tethered to communicationrelays 1102A, 1102B. These communication relays may float on the water'ssurface 914. FIG. 11 is similar to FIG. 10 except that in FIG. 11 theleading drone 902 communicates wirelessly with two sensor drones 1002A,1002B via the communication relays 1102A, 1102B. Each communicationrelay may include an antenna and a flotation device that keeps theantenna near the surface of the water 914.

The communication relay 1102A may communicate with the sensor drone1102A via an underwater relay communication link 1104A and thecommunication relay 1102B may communicate with the sensor drone 1002Bvia an underwater relay communication link 1104B. The underwater relaycommunication links 1104A, 1104B may be over a physical cable (but mayoptionally be wireless in certain embodiments). The leading drone 902may communicate with the communication relay 1102A via an aerial relaycommunication link 1106A. Also, the leading drone 902 may communicatewith the communication relay 1102B via an aerial relay communicationlink 1106B. The aerial relay communication links 1106A, 1106B may bewireless. The aerial relay communication links 1106A, 1106B and theunderwater relay communication links 1104A, 1104B may include any typeof communication protocol from which devices can communicate with eachother, as discussed above. The combination of underwater relaycommunication links 1104A, 1104B and aerial relay communication links1106A, 1106B may function as sensor drone communication links betweenthe respective sensor drones 1002A, 1002B and the leading drone 902.

Advantageously, the communication relays 1102A, 1102B, may improvecommunication between the leading drone 902 and sensor drones 1102A,1102B by translating between communication protocols that are moreamenable for underwater communication with the sensor drones (via theunderwater relay communication links 1104A, 1104B) and communicationprotocols that are more amenable for aerial communications (via theaerial relay communication links 1106A, 1106B).

FIG. 12 illustrates an example of the leading drone 902 communicatingwith the communication relay 1102B servicing multiple sensor drones1002A, 1102B. FIG. 12 is similar to FIG. 11 except that in FIG. 12 thecommunication relay 1102B communicates wirelessly with the two sensordrones 1102A, 1102B over wireless underwater relay communication links1206A, 1206B. The combination of underwater relay communication links1206A, 1206B and aerial relay communication link 1106B may function assensor drone communication links between the respective sensor drones1002A, 1002B and the leading drone 902.

Advantageously, the single communication relay 1102B, may improvecommunication between the leading drone 902 and sensor drones 1102A,1102B by translating between communication protocols that are moreamenable for underwater communication with the sensor drones (via thewireless underwater relay communication links 1206A, 1206B) andcommunication protocols that are more amenable for aerial communications(via the aerial relay communication link 1106B).

FIG. 13 illustrates an example of a leading drone communicating withstationary sensor drones. As introduced above, the base station 1304 maybe anticipated to traverse a base station path 1308 with at least onebase station location 1306 along the base station path 1308. The basestation path 1308 may be along a road 1316 or other geographic landmark.The leading drone 1302 may be configured to traverse a leading dronepath 1312 with at least one relay drone future location 1310. Theleading drone 1302 traversing the leading drone path 1312 may be aheadof the base station 1304 in the direction of the base station path 1308(as indicated with the arrow of the base station path 1308).

The sensor drones 1314A, 1314B may be located proximate to the road 1316and may be stationary while collecting sensor data from the vicinity ofthe sensor drones 1314A, 1314B. Each of the sensor drones 1314A, 1314Bmay communicate over wireless sensor drone communication links 1318A,1318B with the leading drone 1302. Current sensor data and/or aggregatedhistorical sensor data may be sent to the leading drone 1302 when thesensor drone communication links 1318A, 1318B are established with theleading drone 1302. The wireless sensor drone communication links 1318A,1318B may have a limited range from the sensor drones 1314A, 1314B, fromwhich they are centered on. The wireless sensor drone communication link1318A may be established when the leading drone moves within range ofthe wireless sensor drone communication link 1318A centered on thesensor drone 1314A. Also, the wireless sensor drone communication link1318B may be established when the leading drone moves within range ofthe wireless sensor drone communication link 1318B centered on thesensor drone 1314B.

Advantageously, a stationary sensor drone 1314A, 1314B may collectsensor data, with encoded sensor information, over time and send theaggregated sensor drone sensor data to the leading drone 1302 as theleading drone travels within range of the stationary sensor drone'ssensor drone communication link. Accordingly, the leading drone 1302 maycollect historical sensor data from the stationary sensor drone 1314A,1314B that otherwise would not be available to the leading drone 1302due to the leading drone 1302 not having access to sensors in thevicinity of the sensor drone 1314A, 1314B during the time at which thesensor drone 1314A, 1314B was collecting sensor data.

FIG. 14 is a block diagram of example systems utilized in a leadingdrone system. The block diagram 1400 includes at least one base station1406 in communication with at least one leading drone 1402 and at leastone sensor drone 1404. The system of the base stations 1406, leadingdrones 1402 and sensor drones 1404 may be termed as a leading dronenetwork. Optionally, the nodes (base stations, leading drones, sensordrones) of the leading drone network may interact externally with anetwork system 1410 and command center 1430 over a network 1432, such asthe Internet. In the illustrated embodiment of FIG. 14, each of the basestation, leading drone, and sensor drone are illustrated with recedingboxes to note that there may be multiple base stations, leading drones,and/or sensor drones networked and operating together.

The leading drone 1402 can be in communication with at least one sensordrone 1404, at least one base station 1406, and/or with other leadingdrones 1402. Additionally, the leading drone 1402 and/or the sensordrone 1404 can be optionally in communication with the network system1410 or the command center 1430 (e.g., over a network 1432, such as theInternet, or through an intermediate system). The network system 1410,command center 1430 and/or the base station 1406 can determine sensordrone control information, encoded in a sensor drone control signal,describing one or more tasks for performance by the sensor drone (suchas usage of a particular sensor, parameters for a trigger, or task(s) toperform upon occurrence of a trigger). The network system 1410, commandcenter 1430 and/or the base station 1406 can also determine leadingdrone control information, encoded in a leading drone control signal,describing one or more tasks (such as a navigational pattern, usage of aparticular sensor, parameters for a trigger, or tasks to perform uponoccurrence of a trigger) for performance by the leading drone.

The network system 1410 and/or the base station 1406 can include a jobdetermination engine 1412A, 142B that can receive, or obtain,information describing tasks or triggers, and determine information forperformance of the tasks or identification of triggers. In certainembodiments, the job determination engine may include a repository, suchas a data store, that includes various triggers and tasks that may beperformed by a leading drone or a sensor drone, along with associatedmetadata for the triggers or tasks.

The job determination engine 1412A, 1412B can communicate with theapplication engine 1414 for the application engine 1414 to generateinteractive user interfaces (e.g., web pages to be rendered by a basestation) for presentation on a base station 1406 (e.g., on userinterface of the base station). Via the user interface, a user of thebase station 1406 can assign tasks or identify triggers to the leadingdrone 1402 and/or sensor drone 1404 and provide information, such asparameters, associated with a task or trigger.

In certain embodiments, a base station 1406 does not communicate withthe network system 1410 and utilizes a job determination engine 1412Blocally rather than a remote job determination engine 1412A hosted onthe network system for generation of a control signal.

For instance, a user, via the user interface of the application engine1414 at the base station 1406 can assign a task to a leading drone 1402for performance upon detecting a trigger. The trigger may be an eventthat occurs while the leading drone 1402 is operating that reconfiguresthe leading drone 1402 to perform a triggered task. For example, thetrigger event may be detecting a specific property or location that theleading drone 1404 may encounter while traversing its leading dronepath. The triggered task may be to adopt a new leading drone path (e.g.,to collect sensor data while circling the specific property orlocation).

The application engine 142 can process the job information and generatecontrol signals that may be sent to the leading drone as commands forthe leading drone 1402 and/or sensor drone 1404. For instance, thecontrol signal may encode control information that specifies triggers ortasks for the leading drone. The control information may include a taskthat details the leading drone path for the leading drone 1402 based onan anticipated base station path. For example, the control informationcan command the leading drone to navigate according to a zig-zag patternacross the base station path.

The leading drone 1402 can receive the control signal from the basestation 1406 via a leading drone communication link 1418, discussedfurther above. This leading drone communication link 1418 may be over awireless or a wired connection, and may be effectuated using alldirectional antennas, all omnidirectional antennas, or a combination ofomnidirectional and directional antennas. The control signal may includeleading drone control information that controls an aspect of the leadingdrone 1402 or commissions the leading drone 1402 to perform a task, suchas to navigate according to a leading drone path that zig zags acrossthe base station path.

The leading drone 1402 may include a leading drone application engine1420 that can configure the leading drone 1402 to execute the taskidentifiable from the leading drone control signal. The leading dronecontrol signal may also include a sensor drone control signal, where theleading drone 1402 can be configured to pass the sensor drone controlinformation, encoded in a sensor drone control signal, to the sensordrone 1404 via a sensor drone communication link 1424.

The leading drone 1402 can include a navigation control engine 1412 thatcan manage the propulsion mechanisms (e.g., motors, rotors, propellers,and so on) included in the leading drone 1402 to effect the taskidentified in the leading drone control information. Optionally, theleading drone application engine 102 can provide commands (e.g., highlevel commands) to the navigation control engine 1412, which caninterpret or override the leading drone control information from theleading drone control signal. For instance, the leading droneapplication engine 1420 can indicate that the leading drone 1402 is todescend to land at a location due to the leading drone 1402 beingdamaged, and the navigation control engine 1422 can ensure that theleading drone 1402 descends in a substantially vertical direction.

After executing, or as part of, executing the task detailed in theleading drone control information, the leading drone 1402 can send adata signal to the base station 1406. This process may be iterative,such as where the base station 1406 sends additional leading dronecontrol information to the leading drone 1402, after receiving the datasignal. For example, the sensor drone 1404 can provide sensorinformation for the base station 1406. The base station 1406 can combinethe received sensor information (e.g., stitch together images, generatea 3D model of the property, and so on). Based on the combined receivedsensor information, the base station can send updated leading dronecontrol information to the leading drone 1402 for a more detailedinspection of an area identified in the sensor information.

The sensor drone 1402 may include a sensor drone application engine 1420that can configure the sensor drone to execute the task identified inthe sensor drone control information received via the sensor dronecommunication link 1424.

Optionally, the sensor drone 1404 can include a navigation controlengine 1426 that can manage the propulsion mechanisms (e.g., motors,rotors, propellers, and so on) included in the sensor drone 1426 toeffect the task identified in the sensor drone control information. Thesensor drone application engine 1428 can provide commands (e.g., highlevel commands) to the navigation control engine 1426, which caninterpret or override the sensor drone control information. Forinstance, the sensor drone application engine 1428 can indicate that thesensor drone 1426 is to descend to land at a location due to the sensordrone 1404 being damaged, and the navigation control engine 1426 canensure that the sensor drone 1404 descends in a substantially verticaldirection.

After executing, or as part of, executing the task detailed in thesensor drone control information, the sensor drone 1404 can send a datasignal to the leading drone 1402. This data signal may be relayed to thebase station and/or processed by the leading drone 1402. This processmay be iterative, such as where the base station 1406 or leading drone1402 sends additional sensor drone control information, encoded in anadditional sensor drone control signal, to the sensor drone 1404 afterreceiving the data signal. For example, the sensor drone 1404 canprovide sensor information, encoded in a data signal, to the leadingdrone 1402. The leading drone 1402 can combine the received sensor dronesensor information with sensor information collected at the leadingdrone 1402 (e.g., stitch together images, generate a 3D model of theproperty, and so on). Based on the combined sensor information, theleading drone can send updated sensor drone control information to thesensor drone 1404 or send an analysis of the combined sensor informationto the base station 1406.

Optionally, the sensor drone 1404 and/or the leading drone 1402 may bein communication with a command center 1430 over the network 1432. Thecommand center 1430 may directly send sensor drone control informationto a sensor drone and/or leading drone or leading drone controlinformation to a leading drone that overrides control information sentfrom a base station or a leading drone.

FIG. 15 is a flowchart of an example process for determining a leadingdrone path. The process 1500 may be performed by a leading drone, whichmay utilize one or more computers or processors.

The leading drone may identify a base station (block 1502) forinteraction with the leading drone. The base station may be a basestation from which anticipated base station future locations andassociated base station path can be anticipated. The leading drone mayreceive a leading drone control signal that includes leading dronecontrol information that identifies a base station to communicate (orinteract) with. In certain embodiments, the leading drone control signalmay be received at the leading drone from the base station identified inthe leading drone control signal, such as where the base station thatsent the control signal is to pair with the leading drone. In certainembodiments, the leading drone may transmit a leading drone discoverysignal. The leading drone discovery signal may include information forhow a base station is to send the leading drone control signal to theleading drone to identify the base station for interaction with theleading drone.

In certain embodiments, the leading drone control signal may includecriteria from which the leading drone can identify a base station forinteraction with the leading drone. For example, regarding a vehicularbase station, the criteria may be a particular infrared signature for avehicle detected from an infrared sensor accessible to the leadingdrone, a particular vehicle profile detected using edge detection ofvideo data generated from a video camera accessible to the leading droneafter a base station is identified, or a particular location signalperiodically transmitted from a base station and detected from a sensoraccessible to the leading drone.

The leading drone may anticipate base station future locations for theidentified base station to traverse (block 1504). The anticipated basestation future locations may, in the aggregate, form a base stationpath. A processor accessible to the relay drone may utilize the receivedanticipated base station future locations to autonomously construct thebase station path.

In certain embodiments, the anticipated base station future locationsmay be predetermined and received as part of a leading drone controlsignal. For example, the base station may have a geospatial sensor thatsenses where the base station is and, based also on where its intendeddestination is relative to other geospatial information such as a map, anavigational module may plot a navigational path for the base station totraverse over time to arrive at the intended destination. Examplenavigational modules may include the Garmin® Navigator applicationproduced by Garmin Ltd. headquartered in Olathe, Kans. or the Google®Maps Navigation application developed by Google Inc. headquartered inMountain View, Calif.

In certain embodiments, the anticipated base station future locationsmay be determined on the fly or predicted. As introduced above, the basestation's anticipated base station future locations along a base stationpath may be predicted from determining a difference between base stationpast and current locations during a past interval of time (such as overthe last minute) and adding the difference for traversal during a futureinterval of time of the same duration as the past interval of time.Further discussion of predicted base station future locationdetermination is discussed in connection with FIGS. 8 and 16.

Returning to FIG. 15, the leading drone may determine leading dronefuture locations for the leading drone to traverse (block 1506). Theleading drone future locations may, in the aggregate, form a leadingdrone path. The leading drone future locations may be based on the basestation future locations along the base station path. For example, theleading drone future locations may be where the base station isanticipated to be after a period of time or may be at a fixed distanceahead of the base station as the base station traverses base stationfuture locations. The leading drone future locations may be determinedcompletely autonomously without base station input or may besemiautonomous with base station input, via a leading drone controlsignal. For example, a leading drone control signal may instruct theleading drone how to determine leading drone future locations, such asto determine leading drone future locations along a pattern that zigzags across the base station path or along a pattern parallel to thebase station path.

The leading drone may traverse the determined leading drone futurelocations (block 1508). The leading drone may traverse the leading dronefuture locations (and the leading drone path) by executing a navigationcontrol engine that can manage the propulsion mechanisms (e.g., motors,rotors, propellers, and so on) included in the leading drone to traversethe leading drone path.

FIG. 16 is a flowchart of an example process for determining (orpredicting) future locations of a base station on the fly. The process1600 may be performed by a leading drone, which may utilize one or morecomputers or processors.

The leading drone may identify a past location of a base station (block1602). The past location may be detected by the leading drone, viasensors available to the leading drone, at a past time. Alternatively,the past location may be received by the leading drone, such as via aleading drone control signal.

The leading drone may identify a current location of a base station(block 1604). The current location may be detected by the leading drone,via sensors available to the leading drone, at a current time.Alternatively, the current location may be received by the leadingdrone, such as via a leading drone control signal.

The leading drone may determine a difference between the past locationand the current location of the base station (block 1606). Thedifference may include both a direction and a quantity of displacementover a standard interval of time. For example, the difference may be 5meters per second in a north by northwest direction (with no changealong a vertical axis). Stated another way, referring to FIG. 8, thedifference between a past base station location and a current basestation location may be determined to include a past vector 804 of adistance and a direction over a past period of time (e.g., 10 secondspast).

Returning to FIG. 16, the leading drone may determine a future location(block 1608). The difference determined in block 1606 may be applied tothe current location of the leading drone to determine the leading dronefuture location. For example, referring to FIG. 8, the parameters of thepast vector 804 (e.g., distance and direction) may be applied to thecurrent location of the base station 806 as a future vector thatincludes the same distance and direction over a future period of time ofthe same duration as the past period of time (e.g., 10 seconds).Accordingly, a predicted (e.g., anticipated) future base stationlocation may be determined as the end point of the future vector.Additional leading drone future locations at future intervals of timemay be plotted similarly where the future vector is applied iterativelyto base station future locations.

FIG. 17 is a flowchart of an example process for trigger investigation.The process 1600 may be performed by a leading drone, which may utilizeone or more computers or processors.

The leading drone may deploy a sensor accessible to the leading drone atblock 1702. The sensor may be onboard the leading drone. The sensor maybe any sensor configured to collect sensor data from which a triggerevent can be detected. For example, the sensor may be a video cameraconfigured to collect video sensor data.

The leading drone may collect sensor data from the sensor at block 1704.The sensor data may be data generated from the sensor during thesensor's deployment. For example, the sensor data may be video datagenerated from a deployed video camera on the leading drone.

The leading drone may process the sensor data to determine whether atrigger event has occurred based on the sensor data at block 1706. Thesensor data may be processed using a processor onboard or accessible tothe leading drone. The trigger may be an event that initiates atriggered task. For example, the sensor data may be video data fromwhich an unidentified vehicle may be identified. The unidentifiedvehicle may be identified via edge detection or via an unknown vehicleprofile or signature detected in frames of the video data. Theidentification of the unidentified vehicle may be a trigger event.

If a trigger event is identified, the leading drone may perform atriggered task at block 1708. The triggered task may be any task forwhich the leading drone is configured to perform based on the trigger.For example, the task may be to send a detection signal to a basestation indicating trigger event occurrence and/or, when the triggerevent is detection of an unknown vehicle, to circle the unknown vehicle.

If a trigger is not identified, the leading drone may return to block1704 and continue to collect sensor data.

Optionally, the leading drone may return to the leading drone path alongwhich the leading drone may have been traveling during deployment of thesensor in block 1710. The leading drone may return to the leading dronepath at the leading drone future location after interruption by thetriggered task. Alternatively, the leading drone may return to theleading drone path at a location designated for the leading drone totraverse at the time at which the triggered task is complete.

FIG. 18 is a flowchart of an example process for combining leading dronesensor data and sensor drone sensor data. The process 1800 may beperformed by a leading drone, which may utilize one or more computers orprocessors.

The leading drone may deploy a leading drone sensor accessible to theleading drone at block 1802. The leading drone sensor may be onboard theleading drone. The leading drone sensor may be any sensor deployed fromthe leading drone and configured to collect sensor data. For example,the leading drone sensor may be a video camera configured to collectvideo sensor data.

The leading drone may collect leading drone sensor data from the leadingdrone sensor at block 1804. The leading drone sensor data may be datagenerated from the leading drone sensor during the leading dronesensor's deployment. For example, the leading drone sensor data may bevideo sensor data generated from a deployed video camera on the leadingdrone.

The leading drone may establish a sensor drone communication link with asensor drone at block 1806. The sensor drone communication link may beestablished when the leading drone is in range of the sensor dronecommunication link, as discussed above. The sensor drone communicationlink may be persistent, such as when the sensor drone is at a constantdistance from the leading drone as discussed in connection with FIG. 9,or may be non-persistent, as discussed for example in connection withFIG. 13.

The leading drone may receive sensor drone sensor data at block 1808.The sensor drone sensor data may be received via the sensor dronecommunication link. The sensor drone sensor data may be any type ofsensor data collected by the sensor drone via sensors accessible to thesensor drone.

The leading drone may combine leading drone sensor data with sensordrone sensor data in block 1810. This combined sensor data includes notonly leading drone sensor data, but also sensor drone sensor data thatwould not have been accessible to the leading drone withoutcommunication with the sensor drone. The sensor data may be combined invarious ways such as by stitching together images or video to generate a2D or 3D model of a location. Based on the combined sensor data (orsensor information), the leading drone can send mine additional insightsfrom an area investigated by a leading drone sensor from sensor data notcollected by the leading drone sensor.

FIG. 19 illustrates a block diagram of an example system architecturefor a drone for implementing the features and processes describedherein. The drone may be a leading drone or a sensor drone.

A drone primary processing system 1900 can be a system of one or morecomputers, or software executing on a system of one or more computers,which is in communication with, or maintains, one or more databases. Thedrone primary processing system 1900 can be a system of one or moreprocessors 1935, graphics processors 1936, I/O subsystem 1934, logiccircuits, analog circuits, associated volatile and/or non-volatilememory, associated input/output data ports, power ports, etc., and/orone or more software processing executing one or more processors orcomputers. The autopilot system 1930 includes the inertial measurementunit (IMU) 1932, processor 1935, I/O subsystem 1934, GPU 1936, andvarious operating system 1920, and modules 1920-1929. Memory 1918 mayinclude non-volatile memory, such as one or more magnetic disk storagedevices, solid state hard drives, or flash memory. Other volatile memorysuch a RAM, DRAM, SRAM may be used for temporary storage of data whilethe drone is operational. Databases may store information describingdrone navigational operations, navigation plans, contingency events,geofence information, component information, and other information.

The drone processing system may be coupled to one or more sensors, suchas GNSS receivers 1950 (e.g., a GPS, GLONASS, Galileo, or Beidousystem), gyroscopes 1956, accelerometers 1958, temperature sensors 1954pressure sensors (static or differential) 1952, current sensors, voltagesensors, magnetometer, hydrometer, and motor sensors. The drone may usean inertial measurement unit (IMU) 1932 for use in navigation of thedrone. Sensors can be coupled to the processing system, or to controllerboards coupled to the drone processing system. One or more communicationbuses, such as a CAN bus, or signal lines, may couple the various sensorand components.

Various sensors, devices, firmware and other systems may beinterconnected to support multiple functions and operations of thedrone. For example, the drone primary processing system 1900 may usevarious sensors to determine the drone's current geo-spatial location,attitude, altitude, velocity, direction, pitch, roll, yaw and/orairspeed and to pilot the vehicle along a specified route and/or to aspecified location and/or to control the vehicle's attitude, velocity,altitude, and/or airspeed (optionally even when not navigating thevehicle along a specific path or to a specific location).

The navigation control module (also referred to as navigation controlengine) 1922 handles navigation control operations of the drone. Themodule interacts with one or more controllers 1940 that controloperation of motors 1942 and/or actuators 1944. For example, the motorsmay be used for rotation of propellers, and the actuators may be usedfor navigation surface control such as ailerons, rudders, flaps, landinggear, and parachute deployment. The navigational control module 1922 mayinclude a navigational module, introduced above.

The contingency module 1924 monitors and handles contingency events. Forexample, the contingency module may detect that the drone has crossed aborder of a geofence, and then instruct the navigation control module toreturn to a predetermined landing location. Other contingency criteriamay be the detection of a low battery or fuel state, or malfunctioningof an onboard sensor, motor, or a deviation from planned navigation. Theforegoing is not meant to be limiting, as other contingency events maybe detected. In some instances, if equipped on the drone, a parachutemay be deployed if the motors or actuators fail.

The mission module 1929 processes the navigation plan, waypoints, andother associated information with the navigation plan. The missionmodule 1929 works in conjunction with the navigation control module. Forexample, the mission module may send information concerning thenavigation plan to the navigation control module, for example lat/longwaypoints, altitude, navigation velocity, so that the navigation controlmodule can autopilot the drone.

The drone may have various devices or sensors connected to it for datacollection. For example, photographic camera 1949, video cameras,infra-red cameras, multispectral cameras, lidar, radio transceiver,sonar. The drone may additionally have a TCAS (traffic collisionavoidance system). Data collected by the sensors may be stored on thedevice collecting the data, or the data may be stored on non-volatilememory 1918 of the drone processing system 1900.

The drone processing system 1900 may be coupled to various radios, andtransmitters 1959 for manual control of the drone, and for wireless orwired data transmission to and from the drone primary processing system1900, and optionally the drone secondary processing system 1902. Thedrone may use one or more communications subsystems, such as a wirelesscommunication or wired subsystem, to facilitate communication to andfrom the drone. Wireless communication subsystems may include radiotransceivers, and infrared, optical ultrasonic, electromagnetic devices.Wired communication systems may include ports such as Ethernet, USBports, serial ports, or other types of port to establish a wiredconnection to the drone with other devices, such as a ground controlsystem, cloud-based system, or other devices, for example a mobilephone, tablet, personal computer, display monitor, other network-enableddevices. The drone may use a light-weight tethered wire to a ground basestation for communication with the drone. The tethered wire may beremoveably affixed to the drone, for example via a magnetic coupler.

Navigation data logs may be generated by reading various informationfrom the drone sensors and operating system and storing the informationin non-volatile memory. The data logs may include a combination ofvarious data, such as time, altitude, heading, ambient temperature,processor temperatures, pressure, battery level, fuel level, absolute orrelative position, GPS coordinates, pitch, roll, yaw, ground speed,humidity level, velocity, acceleration, and contingency information.This foregoing is not meant to be limiting, and other data may becaptured and stored in the navigation data logs. The navigation datalogs may be stored on a removable media and the media installed onto theground control system. Alternatively, the data logs may be wirelesslytransmitted to the base station, command center or to the networksystem.

Modules, programs or instructions for performing navigation operations,contingency maneuvers, and other functions may be performed with theoperating system. In some implementations, the operating system 1920 canbe a real time operating system (RTOS), UNIX, LINUX, OS X, WINDOWS,ANDROID or other operating system. Additionally, other software modulesand applications may run on the operating system, such as a navigationcontrol module 1922, contingency module 1924, application module 1926,and database module 1928. Typically navigation critical functions willbe performed using the drone processing system 1900. Operating system1920 may include instructions for handling basic system services and forperforming hardware dependent tasks.

In addition to the drone primary processing system 1900, a secondaryprocessing system 1902 may be used to run another operating system toperform other functions. A drone secondary processing system 1902 can bea system of one or more computers, or software executing on a system ofone or more computers, which is in communication with, or maintains, oneor more databases. The drone secondary processing system 1902 can be asystem of one or more processors 1994, graphics processors 1992, I/Osubsystem 1993, logic circuits, analog circuits, associated volatileand/or non-volatile memory, associated input/output data ports, powerports, etc., and/or one or more software processing executing one ormore processors or computers. Memory 1970 may include non-volatilememory, such as one or more magnetic disk storage devices, solid statehard drives, flash memory. Other volatile memory such a RAM, DRAM, SRAMmay be used for storage of data while the drone is operational.

Ideally modules, applications and other functions running on thesecondary processing system 1902 will be non-critical functions innature, that is if the function fails, the drone will still be able tosafely operate. In some implementations, the operating system 1972 canbe based on real time operating system (RTOS), UNIX, LINUX, OS X,WINDOWS, ANDROID or other operating system. Additionally, other softwaremodules and applications may run on the operating system 1972, such asan application module 1978, database module 1980, navigational controlmodule 1974 (which may include a navigational module), and so on (e.g.,modules 1972-1980). Operating system 1902 may include instructions forhandling basic system services and for performing hardware dependenttasks.

Also, controllers 1946 may be used to interact and operate a payloadsensor or device 1948, and other devices such as photographic camera1949, video camera, infra-red camera, multispectral camera, stereocamera pair, lidar, radio transceiver, sonar, laser ranger, altimeter,TCAS (traffic collision avoidance system), ADS-B (Automatic dependentsurveillance-broadcast) transponder. Optionally, the secondaryprocessing system 1902 may have coupled controllers to control payloaddevices.

Each of the processes, methods, and algorithms described in thepreceding sections may be embodied in, and fully or partially automatedby, code modules executed by one or more computer systems or computerprocessors comprising computer hardware. The code modules (or “engines”)may be stored on any type of non-transitory computer-readable medium orcomputer storage device, such as hard drives, solid state memory,optical disc, and/or the like. The systems and modules may also betransmitted as generated data or control signals (for example, as partof a carrier wave or other analog or digital propagated signal) on avariety of computer-readable transmission mediums, includingwireless-based and wired/cable-based mediums, and may take a variety offorms (for example, as part of a single or multiplexed analog signal, oras multiple discrete digital packets or frames). The processes andalgorithms may be implemented partially or wholly inapplication-specific circuitry. The results of the disclosed processesand process steps may be stored, persistently or otherwise, in any typeof non-transitory computer storage such as, for example, volatile ornon-volatile storage.

In general, the terms “engine” and “module”, as used herein, refer tologic embodied in hardware or firmware, or to a collection of softwareinstructions, possibly having entry and exit points, written in aprogramming language, such as, for example, Java, Lua, C or C++. Asoftware module may be compiled and linked into an executable program,installed in a dynamic link library, or may be written in an interpretedprogramming language such as, for example, BASIC, Perl, or Python. Itwill be appreciated that software modules may be callable from othermodules or from themselves, and/or may be invoked in response todetected events or interrupts. Software modules configured for executionon computing devices may be provided on one or more computer readablemedia, such as a compact discs, digital video discs, flash drives, orany other tangible media. Such software code may be stored, partially orfully, on a memory device of the executing computing device. Softwareinstructions may be embedded in firmware, such as an EPROM. It will befurther appreciated that hardware modules may be comprised of connectedlogic units, such as gates and flip-flops, and/or may be comprised ofprogrammable units, such as programmable gate arrays or processors. Themodules described herein are preferably implemented as software modules,but may be represented in hardware or firmware. Generally, the modulesdescribed herein refer to logical modules that may be combined withother modules or divided into sub-modules despite their physicalorganization or storage. Electronic Data Sources can include databases,volatile/non-volatile memory, and any memory system or subsystem thatmaintains information.

The various illustrative logical blocks and modules described inconnection with the embodiments disclosed herein can be implemented orperformed by a machine, such as a general purpose processor, a digitalsignal processor (DSP), an application specific integrated circuit(ASIC), a field programmable gate array (FPGA) or other programmablelogic device, discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. A general purpose processor can be a microprocessor,but in the alternative, the processor can be a controller,microcontroller, or state machine, combinations of the same, or thelike. A processor can include electrical circuitry configured to processcomputer-executable instructions. In another embodiment, a processorincludes an FPGA or other programmable device that performs logicoperations without processing computer-executable instructions. Aprocessor can also be implemented as a combination of computing devices,e.g., a combination of a DSP and a microprocessor, a plurality ofmicroprocessors, one or more microprocessors in conjunction with a DSPcore, or any other such configuration. Although described hereinprimarily with respect to digital technology, a processor may alsoinclude primarily analog components. For example, some or all of thesignal processing algorithms described herein may be implemented inanalog circuitry or mixed analog and digital circuitry. A computingenvironment can include any type of computer system, including, but notlimited to, a computer system based on a microprocessor, a mainframecomputer, a digital signal processor, a portable computing device, adevice controller, or a computational engine within an appliance, toname a few.

The elements of a method, process, or algorithm described in connectionwith the embodiments disclosed herein can be embodied directly inhardware, in a software module stored in one or more memory devices andexecuted by one or more processors, or in a combination of the two. Asoftware module can reside in RAM memory, flash memory, ROM memory,EPROM memory, EEPROM memory, registers, hard disk, a removable disk, aCD-ROM, or any other form of non-transitory computer-readable storagemedium, media, or physical computer storage known in the art. An examplestorage medium can be coupled to the processor such that the processorcan read information from, and write information to, the storage medium.In the alternative, the storage medium can be integral to the processor.The storage medium can be volatile or nonvolatile. The processor and thestorage medium can reside in an ASIC. The ASIC can reside in a userterminal. In the alternative, the processor and the storage medium canreside as discrete components in a user terminal.

The various features and processes described above may be usedindependently of one another, or may be combined in various ways. Allpossible combinations and subcombinations are intended to fall withinthe scope of this disclosure. In addition, certain method or processblocks may be omitted in some implementations. The methods and processesdescribed herein are also not limited to any particular sequence, andthe blocks or states relating thereto can be performed in othersequences that are appropriate. For example, described blocks or statesmay be performed in an order other than that specifically disclosed, ormultiple blocks or states may be combined in a single block or state.The example blocks or states may be performed in serial, in parallel, orin some other manner. Blocks or states may be added to or removed fromthe disclosed example embodiments. The example systems and componentsdescribed herein may be configured differently than described. Forexample, elements may be added to, removed from, or rearranged comparedto the disclosed example embodiments.

Conditional language used herein, such as, among others, “can,” “could,”“might,” “may,” “for example,” and the like, unless specifically statedotherwise, or otherwise understood within the context as used, isgenerally intended to convey that certain embodiments include, whileother embodiments do not include, certain features, elements and/orsteps. Thus, such conditional language is not generally intended toimply that features, elements and/or steps are in any way required forone or more embodiments or that one or more embodiments necessarilyinclude logic for deciding, with or without author input or prompting,whether these features, elements and/or steps are included or are to beperformed in any particular embodiment. The terms “comprising,”“including,” “having,” and the like are synonymous and are usedinclusively, in an open-ended fashion, and do not exclude additionalelements, features, acts, operations, and so forth. Also, the term “or”is used in its inclusive sense (and not in its exclusive sense) so thatwhen used, for example, to connect a list of elements, the term “or”means one, some, or all of the elements in the list. Conjunctivelanguage such as the phrase “at least one of X, Y and Z,” unlessspecifically stated otherwise, is otherwise understood with the contextas used in general to convey that an item, term, etc. may be either X, Yor Z. Thus, such conjunctive language is not generally intended to implythat certain embodiments require at least one of X, at least one of Yand at least one of Z to each be present.

The term “a” as used herein should be given an inclusive rather thanexclusive interpretation. For example, unless specifically noted, theterm “a” should not be understood to mean “exactly one” or “one and onlyone”; instead, the term “a” means “one or more” or “at least one,”whether used in the claims or elsewhere in the specification andregardless of uses of quantifiers such as “at least one,” “one or more,”or “a plurality” elsewhere in the claims or specification.

The term “comprising” as used herein should be given an inclusive ratherthan exclusive interpretation. For example, a general purpose computercomprising one or more processors should not be interpreted as excludingother computer components, and may possibly include such components asmemory, input/output devices, and/or network interfaces, among others.While certain example embodiments have been described, these embodimentshave been presented by way of example only, and are not intended tolimit the scope of the disclosure. Thus, nothing in the foregoingdescription is intended to imply that any particular element, feature,characteristic, step, module, or block is necessary or indispensable.Indeed, the novel methods and systems described herein may be embodiedin a variety of other forms; furthermore, various omissions,substitutions, and changes in the form of the methods and systemsdescribed herein may be made without departing from the spirit of theinventions disclosed herein. The accompanying claims and theirequivalents are intended to cover such forms or modifications as wouldfall within the scope and spirit of certain of the inventions disclosedherein.

Any process descriptions, elements, or blocks in the flow diagramsdescribed herein and/or depicted in the attached figures should beunderstood as potentially representing modules, segments, or portions ofcode which include one or more executable instructions for implementingspecific logical functions or steps in the process. Alternateimplementations are included within the scope of the embodimentsdescribed herein in which elements or functions may be deleted, executedout of order from that shown or discussed, including substantiallyconcurrently or in reverse order, depending on the functionalityinvolved, as would be understood by those skilled in the art.

It should be emphasized that many variations and modifications may bemade to the above-described embodiments, the elements of which are to beunderstood as being among other acceptable examples. All suchmodifications and variations are intended to be included herein withinthe scope of this disclosure. The foregoing description details certainembodiments of the invention. It will be appreciated, however, that nomatter how detailed the foregoing appears in text, the invention can bepracticed in many ways. As is also stated above, it should be noted thatthe use of particular terminology when describing certain features oraspects of the invention should not be taken to imply that theterminology is being re-defined herein to be restricted to including anyspecific characteristics of the features or aspects of the inventionwith which that terminology is associated.

It is to be understood that not necessarily all objects or advantagesmay be achieved in accordance with any particular embodiment describedherein. Thus, for example, those skilled in the art will recognize thatcertain embodiments may be configured to operate in a manner thatachieves or optimizes one advantage or group of advantages as taughtherein without necessarily achieving other objects or advantages as maybe taught or suggested herein.

What is claimed is:
 1. A system comprising: a base station in the formof a watercraft having a pre-determined path of travel for the basestation to traverse over water towards a target location; an unmannedaerial drone is configured to receive an information on thepre-determined path of travel for the base station and autonomouslycalculate an aerial drone path that directly correlates with thepre-determined path of travel for the base station; said unmanned aerialdrone is configured to autonomously travel on said aerial drone path,and wherein the unmanned aerial drone is at a fixed distance from thebase station during travel; said unmanned aerial drone is configured tocollect aerial sensor data from the target location; and a submerseddrone to traverse underwater and physically tethered to the aerial droneand is configured to collect underwater sensor data from the targetlocation, the submersed drone is configured to send the underwatersensor data to the aerial drone, the aerial drone is configured toproduce target location data from the aerial sensor data and theunderwater sensor data.
 2. The system of claim 1, wherein a cableconnects the submersed drone with the unmanned aerial drone.
 3. Thesystem of claim 2, wherein the unmanned aerial drone tows the submerseddrone via the cable.
 4. The system of claim 1, the submersed drone isconfigured to move along a submersed drone path based on the aerialdrone path.
 5. The system of claim 4, wherein the submersed drone isconfigured to move along the submersed drone path behind the unmannedaerial drone.
 6. The system of claim 1, wherein the submersed drone isself-propelled.
 7. The system of claim 1, wherein the unmanned aerialdrone is configured to send the target location data to the basestation.
 8. The system of claim 1, wherein the submersed drone isconfigured to move along a submersed drone path based on a movement ofthe unmanned aerial drone.
 9. The system of claim 1, wherein thesubmersed drone is configured to move to the target location.
 10. Thesystem of claim 1, wherein the unmanned aerial drone is configured toidentify a base station configured to move from a current location;determine a future location of the base station; and move to an aerialdrone location relative to the future location.
 11. The system of claim10, wherein the aerial drone location is at the future location.
 12. Thesystem of claim 10, wherein the unmanned aerial drone is configured toreceive a control signal from the base station comprising the futurelocation.
 13. The system of claim 10, wherein the unmanned aerial droneis configured to determine the future location based on the currentlocation.